One of the hardest debates is deciding between a code-first API approach or design-first. In an ideal world, we would deliver our APIs at maximum velocity, with minimum maintenance. To maintain the appropriate API consumption, the world has looked at Amazon’s API Gateway as the orchestration of resources to create, deploy, and manage APIs at scale. One of the biggest challenges users face when using any API Gateway is the lack of consistency and standardization throughout the API experience.

In the past decade, chat apps have gone from being a disruptive new technology to something we use every day. Today, WhatsApp boasts over 2 billion daily active users, by far the market leader, followed by WeChat with 1.3 billion and Facebook Messenger at just under 1 billion. Chat apps, put simply, are going nowhere. In that time, customers have come to expect a consistent experience across their chat apps – and a core set of functionality has evolved across all major providers.

APIs have revolutionized every industry. They fuel digital transformation and power the web, making up more than 83% of global internet traffic. And API adoption will only grow, with AI, Web3, and decentralization only further driving API usage and integration. But these sometimes-overlooked enablers of connectivity and communication present a serious security challenge: APIs are increasingly in the crosshairs of cyber-attackers.

Kong will crash on the ARM64 platform (the machine with Mac M1/M2 chips or any ARM64 platform). The error message shows the crash is triggered by the SIGILL signal, which means there is an illegal instruction in the Kong binary code. And it turns out to be caused by an error in the LuaJIT ARM64 JIT compiler. This post records how the error is found and fixed.

Step right up, ladies and gentlemen, and witness the grand spectacle of the digital age! In a world where data is king, where information reigns supreme, and cloud data warehouses are multiplying like rabbits, there's a technology initiative like no other— data warehouse modernization! This article is the second in the series "Seven Data Integration and Quality Scenarios for Qlik and Talend," and answers everything you wanted to know about data warehouse modernization but were afraid to ask.

You’ve probably heard of the “shift-left” mantra as it echoes throughout the tech industry. And if you haven’t, let me be the first to update you that you’ve been living under a rock. Like a real rock, not even a figurative one. In all seriousness, ‘shift-left’ has shaken things up quite a bit in the tech industry, bringing with it a paradigm shift in how we approach software development.

Software testing and quality engineering (QE) are critical aspects of successful digital delivery in today’s fast-paced digital landscape. Many digital enterprises face challenges in achieving frictionless experiences, efficiency, and effectiveness in their QE journey.